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Given that you have the LIDAR DEM, you should use the streams derived from it. That guarantees perfect registration.
The crux of the idea is to estimate mean slopes in terms of the elevations at the ends of the segments.
One of the easiest procedures is to "explode" the stream network into its component unbranched arcs. Convert the collection into a ...

Convert your stream vectors to raster with a value of 1 and the same extent and cellsize as your DEM. In the Raster Calculator use a map algebra expression something along the lines of:
Con("rivers"==1, "DEM" - 1, "DEM")
If you want to burn in the streams more than 1 elevation unit, change "DEM" - 1 to "DEM" - a bigger value.
To implement the Whitebox ...

You are correct that distortions in the projection can bias flow direction (and flow accumulation) estimates. (Using "unprojected" data is tantamount to using the highly distorting Plate Carree projection.)
For merely delineating basins, though, there actually is little problem: although the flow directions and flow amounts will be wrong, the projection ...

While Jacub is correct that a stream ordering technique is your best bet for being able to represent stream magnitude or discharge, since the position in the network is a surrogate for these two stream characteristics, I would argue that you want to avoid using Horton-Strahler stream order for this purpose. It is seriously deficient in these applications, ...

You can classify the streams using, among others, the Strahler Stream Ordering method.
In the Strahler method, all links without any tributaries are assigned
an order of 1 and are referred to as first order.
The stream order increases when streams of the same order intersect.
Therefore, the intersection of two first-order links will create a
...

Whitebox GAT (open-source hydrology and remote sensing package) has a method by this name in its Hydrology utilities. Whitebox is unique in that it exposes the source code and algorithms used by the analysis via the UI (note the View Code button). Even if you intend to isolate your procedures to ArcGIS, there may be some benefits to experimenting with ...

First, you need to calculate at least the slope. F.ex I have the following data:
Then put the correct data as variables to the module:
And at last you should get the result:
UPDATE
With Catchment Area as input
the results are:

The analysis has already been done in a reply to the antecedent question, but perhaps an illustration will help.
There are two major components of error: the "d8" algorithm, which represents flows in only eight cardinal directions, and the effect of projection (or lack of it). Let's focus on the latter, because this seems to be the principal concern.
The ...

As someone who did feature capture from imagery for a while, I would caution you against expecting a pool at a spring. The majority of the ones I've encountered (both in capture and on the ground in person) don't have one. We often referred to ancillary sources to suggest/confirm a spring. Depending on your purposes, USGS quad sheets or hydrography datasets ...

The slope is obtained by extracting the elevations at the sample point and the point 100 meters upgradient along the main stream (and then dividing their difference by 100). Consider these criteria for finding the upstream point:
It must lie on a stream.
It must be upstream of the sample point.
The stream distance to the sample point must be 100 meters.
...

It seems that there are two things going on here. First, your tiles are not seamless, in that in the areas of overlap at the edges of the tiles, the elevations are not identical. I can confirm this as I digitized several points along the overlapping area and extracted the elevations in both raster DEMs and found this:
In the case of the two tiles that you ...

Yep, turns out I wasn't honoring the wisdom of the beginner's mind and I jumped right to an assumption that my problem was way more complex than simply not having run the Set Flow Direction tool. Entries in the attribute table of the NHDFlowline file suggest that "WITH_DIGITIZED_DIRECTION" is the right parameter to go with - and it seems to check out ...

Tapering will emerge from an appropriate kernel smooth of a transformed streamflow grid. For a start, consider using the square root of stream flow and use an exponential kernel: the bandwidth of the kernel will determine the apparent width on the map.
Here is a sample workflow using operations commonly found in raster GISes such as Spatial Analyst, ...

I can't speak much on GRASS specifically, but it looks like what you're trying to do here is develop flow direction and accumulation grids - I'm pretty sure GRASS already has that functionality built-in.
Once you've developed those grids, you can use a regression equation (the USGS develops these: http://water.usgs.gov/osw/programs/nss/pubs.html#wv) to ...

You could perform a watershed analysis yourself, but its a time consuming process. One good source of existing river catchment data is the HydroSHEDS project, which provides high resolution basins for much of the globe, including the UK.

The trick is to Google "UK river catchment map". (Other combinations that include "watershed" don't work.) You will find
River basin management plan documents.
River basin district maps (downloadable files).
An interactive map.
Maps by the UK Environment Agency.
Scottish river basin maps and data.
A search involving "watershed" did turn up a historical ...

It wasn't clear from the description of your project whether you are trying to model the passage of a flood wave through a 2-D flow grid (i.e., the change in inundation area as a function of time as the flood passes from upstream to downstream), or whether your output is to show the highest flood elevation at any given point caused by a single flooding event ...

Recompute the flow accumulation by setting the input ("rainfall area") to 1 within the cells of a given land use and 0 elsewhere. Extract the values at the stations (one operation via the "extract values to points" tool). Multiply these results by the squared cellsize to estimate the areas. Repeat for each land type. Join the results on the station ...

So through discussions on another forum I was able to figure out why the standalone script was running so terribly slow. This is because I did not have the gp.ScratchWorkspace property set. Once I set that to mirror my ArcToolBox General Environment setting using the same directory, I was able to run the Python script from the command line in approx. 6 ...

If you don't find a map, SAGA GIS has a module called watershed basins that uses a dem and the channel network (your rivers). If you use a coarse dem this goes fast.
http://www.saga-gis.org/saga_modules_doc/ta_channels/index.html

I'm afraid you are lost with QGIS. According to the Readme.doc, the data is in Arcgis 9.3 format.
QGIS and GDAL only support gdb file databases written by Arcgis 10 and above.
As an alternative, you can download the data from NHD Plus in other formats too. These are shapefiles and Arcinfo hdr raster files, depending on the topic. Both formats can be read ...

If you have tiny streams then you will want to have satellite imagery with better resolution than Landsat (30 meter pixels). However, Landsat has the best historical coverage. I would do a combination of imagery and elevation (DEM) data. Using a DEM to make a hillshade, or some hydro analysis (flow direction) will provide you a great combination of options ...

In general, to create a map of sinkholes using a DEM, you would first fill the topographic depressions (sinkholes) then difference the original DEM from the filled DEM. This gives you 'depth in sink' but if you simply want a Boolean sink map, reclass the depth map such that 1 is assigned to all values greater than 0. The tool in GRASS GIS to fill depressions ...

Suggest you try building a virtual raster from the DEM TIFFs: Raster -> Miscellaneous -> Build Virtual Raster (Catalog). It seems to work with your sample data. Sorry, I just had to put some hillshade on the result. N.

Landsat imagery would be helpful. Different bands can be utilized separately or together depending on your needs, in your case delineating water and land boundaries would be near infared. If the streams are as tiny as stated, they may not appear due to the resolution or lack thereof.
Some links:
...

Ja Geo,
The Pfafsteter method requires that your basin/drainage network is topologically correct.
Arcgis have several topologically rules that can help you with that!
Once you have the basin/drainage network you can implement it python with numpy. It has several functions to help find index and etc.
A simpler way is to use python list objects. They are a ...

The short answer is no - the question is basically about automated feature extraction from imagery.
Some of the data that goes into the quad sheets is available as vector data. The National Hydrography Dataset is where you'd start looking. You can grab the point layer, which has stream guages, dams, and 'other' (including seeps/springs) from the National ...

I have spent many years surveying rivers in the UK and have visited the sources of many streams. My experience in the UK a spring is rarely a pool of standing water but are "flushes", basically water seeping out of the ground. Springs could be swampy areas or heathland dominated typically with Juncus. But we do have the classic water bubbling out of the ...